Cow 1440 stood on the straw pack next to where I was feeding a newborn calf and where I could easily observe her. The cow was gaunt with dull eyes and droopy ears and a very slack udder. She had calved with twins about a week ago, had a difficult birth and wasn’t eating despite being drenched.
“She has a DA,” I thought, and mentioned it to Mike.
The next day I drove to Sioux Falls, South Dakota, for the National Holstein Convention and Dairy Innovations Summit, a first-time added item to the agenda for the week’s activities, contests, tours and Holstein Association business meetings. I was attending as a volunteer to help with Junior Holstein activities.
When I returned home, 1440 had undergone DA surgery and was recovering. Did it take an expert cow person to observe she needed care? No. Anyone who works with cows knew she did, so she was diagnosed and treated.
I thought about the cow people as I sat at the Data and Innovations Summit listening to the many excellent talks about big data and how it can be utilized on dairy farms of any size. It struck me that the conference was set at the Holstein Convention where the people in attendance probably take far more interest in their cows via registrations, pedigrees, cow family development, sire stacks, embryo transfer and all the marketing activities that are involved. They are true cow people, I thought, as I remembered the stories I used to write about them.
But cow people also know when their animals are sick, in heat or off feed. Perhaps as dairies grow in size, and fewer people have the individual cow skills, more data can be very helpful in making management decisions. Capturing, sorting and analyzing data, called big data or data analytics, can help managers to determine what is best for cow health, comfort, reproduction, milk quality, grouping, feeding and many other day-to-day tasks.
The conference did a deep dive into the realm of data and all it entails. Dr. Jeffrey Bewley, Holstein Association USA analytics and innovation scientist, who works with the WKU Smart Holstein Lab, walked us through the types of data and how it could be used. The purpose of the new lab is to figure out devices and what the data means. Technological innovations include cloud computing, robots, sensors, drones, image analysis, visual analytics, GPS, artificial intelligence, blockchain technology, genomics, metabolomics and advanced data analytics.
The history of cow record keeping and dairy technology has unfolded through the decades, and on-farm records have existed from the beginning of cow milking, Bewley said. Cow activity monitors, where data from cow monitors is communicated wirelessly to evaluate the cow’s status through laptops or smartphones, have existed since the 1990s.
“Analytics is the next big scientific breakthrough,” Bewley said. “How we statistically look at data is new. There are external drivers.”
Interspersed throughout the conference were video technology introductions of data gathering systems and devices, such as iYOTAH Solutions, VES-Artex, CowManager, SomaDetect, FeedVal and many more. The people marketing and supporting these systems could be accessed at the conference during breaks and discussions were enlightening.
Another speaker, Dr. Michael Overton, Zoetis, discussed the do’s and don’ts of interpreting farm data. His point was that data equals bits of information, but that it is not information itself. The data needs to be properly processed, organized and interpreted well. I imagine there is a lack of time to evaluate data or a dedicated data manager on many dairies.
 He cautioned that mistakes can and do happen in data collection and entry. Did cow No. 202 really have 249 pounds of milk? Outliers change averages and perspectives, Overton said.
Other conference talks contained salient points about the need to carefully determine which data points are most useful to management tasks:
– The more decisions you can make with a piece of data, the better.
– Future success depends on anticipating how data can be used across the operation, and the data providers should be challenged to help you do more with, or extract value from, the data.
– You must ask for help from data providers.
Getting back to our cow 1440. Let’s suppose that according to her genetic data, 1440 perhaps was not likely to have a DA. So then, because of her twinning and calving troubles, management or environmental factors overwhelmed the genetic-based outcomes for her. She needed extra care and was drenched, given special needs space, etc. Still, she had a DA and that is part of dairying.
No matter the data you have to work with to shape the management strategies on your dairy, and no matter how many cows you milk, success likely relies in part on the way you treat cows individually. However, I look forward to tapping into the many new technologies that are now here to help make good and useful cow-related decisions.
    Jean dairy farms with her husband, Rolf, and brother-in-law, Mike, and children Emily, Matthias and Leif. They farm near St. Peter, Minnesota, in Norseland, where she is still trying to fit in with the Norwegians and Swedes. They milk 200 cows and farm 650 acres. She can be reached at